Mass spectrometry is a widely used technique that helps scientists determine what molecules are present in a sample and how much of each there is. However, most current instruments examine molecules one at a time or in very small groups. This approach can be slow, expensive, and prone to missing rare but important molecules hidden among more abundant ones.
A more advanced version of this technology could eventually allow researchers to capture the complete molecular makeup of a single cell, monitor thousands of chemical reactions simultaneously, and speed up processes such as drug discovery.
A new study describes an early step toward that goal. Researchers have developed a prototype called MultiQ-IT that can process large numbers of molecules at the same time. The work provides a framework for building faster and more sensitive instruments, potentially enabling a shift similar to the transformations seen in genomics and computing.
“What revolutionized DNA sequencing wasn’t any change in the underlying chemistry. That’s remained fundamentally the same,” says Brian T. Chait, Laboratory of Mass Spectrometry and Gaseous Ion Chemistry at Rockefeller. “It was the ability to run so many chemical reactions in parallel, which took genome sequencing from a billion-dollar effort to something that costs around $100. The same thing happened in computing with GPUs. And that’s what we’re trying to do with mass spectrometry.”
The Bottleneck in Modern Mass Spectrometry
Mass spectrometry dates back to around 1913 and has become one of biology’s most important analytical methods. It works by ionizing molecules, meaning giving them an electric charge, and then measuring their mass-to-charge ratio to identify and quantify them. Despite its capabilities, most systems still operate sequentially, analyzing only one or a few types of ions at a time. This limits their ability to detect rare molecules in complex biological samples.
“It’s a wonderful technique — you can do unimaginably wonderful, analytical things with it,” Chait says. “But I was always a little frustrated by its limitations. I knew, in my heart, it could be better.”
Improving this limitation could have a major impact on fields such as single-cell proteomics and metabolomics, which aim to measure all proteins or metabolites within a single cell. Unlike DNA, these molecules cannot be copied or amplified, and some may be millions of times less abundant than others. While mass spectrometry is already used in these areas, its current sensitivity often falls short when trying to detect faint signals among overwhelming background noise.
To address this challenge, Chait and his team believed the solution would be “massive parallelization,” a concept that previously transformed computing and DNA sequencing. In computing, breaking large problems into many smaller tasks and processing them simultaneously with graphics processing units, or GPUs, led to major performance gains. DNA sequencing followed a similar path, allowing millions of reactions to be analyzed at once at much lower cost.
“It was a very obvious idea,” says Andrew Krutchinsky, a senior research associate in the lab. “But how to do it with mass spectrometry wasn’t obvious.”
A Parallel Approach Inspired by Cells
The concept behind MultiQ-IT emerged from long-term research on how molecules move in and out of a cell’s nucleus through structures known as nuclear pore complexes. These structures distribute traffic across many small openings instead of forcing everything through a single path. The researchers wondered if mass spectrometry could be redesigned to work in a similar way.
The result is a newly designed ion-trapping chamber intended to replace a key part of traditional mass spectrometers. This cube-shaped device contains hundreds of small, electrically controlled openings. Inside the chamber, ions collide with gas molecules, slow down, and move randomly. This allows the system to sort, hold, and direct multiple groups of ions at the same time instead of processing them sequentially.
The team expanded the design from just six openings to more than 1,000, testing how effectively ions could be managed and separated. They showed that a single incoming stream of ions could be divided into multiple parallel streams for simultaneous analysis.
Handling Billions of Molecules at Once
The prototype delivered impressive performance. A version with 486 ports could hold up to ten billion charges at once, which is about a thousand times more than conventional ion traps.
The system also improves detection by allowing common background molecules to escape while keeping rarer, more informative ones inside. This increased the signal-to-noise ratio by as much as 100-fold, making it possible to detect proteins that were previously undetectable. To achieve this, the researchers applied a small electrical voltage barrier at the exits of the trap. Singly charged ions could escape, while multiply charged ions, which are often more biologically important, remained trapped.
In a larger design with 1,134 ports, only 39 open ports were needed to reach half of the system’s maximum filtering efficiency, similar to how cells use a limited number of nuclear pores to manage molecular traffic. The researchers also found that spreading ions across many channels reduces the strong electrical repulsion that occurs when large numbers of similarly charged particles are packed into a small space.
This boost in sensitivity could improve the detection of low abundance crosslinked peptides, which are valuable for mapping the structures of large protein complexes. “The least abundant things can be more important than the more abundant things,” Krutchinsky says.
A Blueprint for Future Instruments
At this stage, MultiQ-IT is not yet a finished commercial product but rather a proof of concept showing what is achievable. The researchers see it as a foundational design that could eventually be developed into practical tools for clinical and laboratory use.
“There was a lot of development between the discovery of a reaction for sequencing DNA and modern genomics; decades between the first transistor and putting a billion transistors on a chip,” Chait says. “In both cases, someone first had to show it could be done, and then industry took over. I think we’ve shown one way mass spectrometry can be done more efficiently.”